Exploiting Proximity-Aware Tasks for Embodied Social Navigation

Enrico Cancelli, Tommaso Campari, Luciano Serafini, Angel X. Chang, Lamberto Ballan; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023, pp. 10957-10967


Learning how to navigate among humans in an occluded and spatially constrained indoor environment, is a key ability required to embodied agents to be integrated into our society. In this paper, we propose an end-to-end architecture that exploits Proximity-Aware Tasks (referred as to Risk and Proximity Compass) to inject into a reinforcement learning navigation policy the ability to infer common-sense social behaviours. To this end, our tasks exploit the notion of immediate and future dangers of collision. Furthermore, we propose an evaluation protocol specifically designed for the Social Navigation Task in simulated environments. This is done to capture fine-grained features and characteristics of the policy by analyzing the minimal unit of human-robot spatial interaction, called Encounter. We validate our approach on Gibson4+ and Habitat-Matterport3D datasets.

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[pdf] [arXiv]
@InProceedings{Cancelli_2023_ICCV, author = {Cancelli, Enrico and Campari, Tommaso and Serafini, Luciano and Chang, Angel X. and Ballan, Lamberto}, title = {Exploiting Proximity-Aware Tasks for Embodied Social Navigation}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, month = {October}, year = {2023}, pages = {10957-10967} }